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        <h3 id="一、子查询"><a href="#一、子查询" class="headerlink" title="一、子查询"></a>一、子查询</h3><p>子查询，又称之为内查询，是一种嵌套在其他 Sql 查询的 Where 子句中的查询。</p>
<ul>
<li>子查询必须包含在圆括号内，并且不能使用 ORDER BY 进行排序。</li>
</ul>
<p><strong>实例 1</strong> ：</p>
<div class="highlight-box"autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false" contenteditable="true"data-rel="SQL"><figure class="iseeu highlight /sql"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">SELECT</span> * <span class="keyword">FROM</span> a <span class="keyword">WHERE</span> <span class="keyword">id</span> <span class="keyword">IN</span> (<span class="keyword">SELECT</span> a_id <span class="keyword">FROM</span> b);</span><br></pre></td></tr></table></figure></div>

<p>只能查询到 a 表内容，以子查询结果作为查询条件。</p>
<a id="more"></a>

<p><strong>实例 2</strong> ：</p>
<div class="highlight-box"autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false" contenteditable="true"data-rel="SQL"><figure class="iseeu highlight /sql"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">SELECT</span> * <span class="keyword">FROM</span> a, (<span class="keyword">SELECT</span> a_id,remark <span class="keyword">FROM</span> b)b <span class="keyword">WHERE</span> a.id = b.a_id ;</span><br></pre></td></tr></table></figure></div>

<p>这种子查询格式是基于笛卡尔积，所以两表数据都可以查询到，但子查询结果中必须包含关联字段，且子查询表需要设置别名。最后要加上过滤条件过滤查询结果才能得到理想数据。</p>
<p>因为子查询结果可以控制第二个表乘积后的大小，相对于上面两个表直接乘积查询速度会快一点。</p>
<h3 id="二、笛卡尔积查询"><a href="#二、笛卡尔积查询" class="headerlink" title="二、笛卡尔积查询"></a>二、笛卡尔积查询</h3><p>笛卡尔乘积是指在数学中，两个集合<em>X</em>和<em>Y</em>的笛卡尔积（Cartesian product），又称直积，表示为<em>X</em> × <em>Y</em>。</p>
<p>笛卡尔积在数据库查询中的应用：</p>
<ol>
<li>先确定数据要用到哪些表。</li>
<li>将多个表先通过笛卡尔积生成一个查询结果集。</li>
<li>然后去除不符合逻辑的数据（根据两个表的关系去掉）。</li>
<li>最后当做是一个虚拟表一样来加上过滤条件得出查询数据。</li>
</ol>
<p><strong>实例 1</strong>：不使用查询条件过滤结果</p>
<div class="highlight-box"autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false" contenteditable="true"data-rel="SQL"><figure class="iseeu highlight /sql"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">SELECT</span> * <span class="keyword">FROM</span> a,b</span><br></pre></td></tr></table></figure></div>



<p><strong>实例 2</strong>：使用查询条件过滤结果</p>
<blockquote>
<p>a 表的字段 id 与 b 表的字段 a_id 互为关联字段</p>
</blockquote>
<div class="highlight-box"autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false" contenteditable="true"data-rel="SQL"><figure class="iseeu highlight /sql"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">SELECT</span> * <span class="keyword">FROM</span> a,b <span class="keyword">WHERE</span> a.id = b.a_id</span><br></pre></td></tr></table></figure></div>



<p>这种查询方式简单粗暴，它会先乘积生成两张表的查询结果集，然后再通过限制条件去过滤；因此，在数据量大的时候，查询速度会很慢</p>
<h3 id="三、连接查询（join-on）"><a href="#三、连接查询（join-on）" class="headerlink" title="三、连接查询（join on）"></a>三、连接查询（join on）</h3><p>JOIN 连接用于把来自两个或多个表的行结合起来。</p>
<ul>
<li>其连接方式又分<strong>交叉连接</strong>、<strong>外连接</strong>和<strong>内连接</strong>。</li>
</ul>
<h4 id="1、交叉连接（cross-join）"><a href="#1、交叉连接（cross-join）" class="headerlink" title="1、交叉连接（cross join）"></a>1、交叉连接（cross join）</h4><p>和笛卡尔积查询相似，交叉连接是基于笛卡尔积的连接方式，它实际上是把两个表乘起来，所以又称为笛卡尔积连接。交叉连接不能使用连接条件，但可以使用查询条件。</p>
<p><strong>实例</strong>1：</p>
<div class="highlight-box"autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false" contenteditable="true"data-rel="SQL"><figure class="iseeu highlight /sql"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">SELECT</span> * <span class="keyword">FROM</span> a <span class="keyword">CROSS</span> <span class="keyword">JOIN</span> b</span><br></pre></td></tr></table></figure></div>

<p><strong>实例 2</strong>：</p>
<figure class="highlight"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">ELECT * FROM a CROSS JOIN b WHERE a.id = b.student_id</span><br></pre></td></tr></table></figure>





<h4 id="2、外连接（）"><a href="#2、外连接（）" class="headerlink" title="2、外连接（）"></a>2、外连接（）</h4><p>外连接分为两种，一种是左连接（left join）和右连接（right join）。</p>
<h5 id="2-1、左外连接（left-join）"><a href="#2-1、左外连接（left-join）" class="headerlink" title="2.1、左外连接（left join）"></a>2.1、左外连接（left join）</h5><p>左连接全称为左外连接，是外连接的一种。是以左表为基础，根据ON后给出的两表的条件将两表连接起来。结果会将左表所有的查询信息列出，而右表只返回 ON 后条件与左表满足的部分，右表不存在的字段数据用 null 代替。</p>
<ul>
<li>关键词为 LEFT JOIN 或 LEFT OUTER JOIN</li>
</ul>
<p><strong>实例</strong>：</p>
<div class="highlight-box"autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false" contenteditable="true"data-rel="SQL"><figure class="iseeu highlight /sql"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">SELECT</span> * <span class="keyword">FROM</span> a <span class="keyword">LEFT</span> <span class="keyword">JOIN</span> b <span class="keyword">ON</span> a.id = b.a_id ;</span><br></pre></td></tr></table></figure></div>

<table>
<thead>
<tr>
<th>id</th>
<th>name</th>
<th>a_id</th>
<th>age</th>
</tr>
</thead>
<tbody><tr>
<td>1</td>
<td>张三</td>
<td>1</td>
<td>少年</td>
</tr>
<tr>
<td>2</td>
<td>李四</td>
<td>2</td>
<td>青年</td>
</tr>
<tr>
<td>3</td>
<td>王五</td>
<td>null</td>
<td>null</td>
</tr>
</tbody></table>
<h5 id="2-2、右外连接（right-join）"><a href="#2-2、右外连接（right-join）" class="headerlink" title="2.2、右外连接（right join）"></a>2.2、右外连接（right join）</h5><p>右连接全称为右外连接，是外连接的一种。是以右表为基础，根据ON后给出的两表的条件将两表连接起来。结果会将右表所有的查询信息列出，而左表只列出 ON 后条件与右表满足的部分，左表不存在的字段数据用null代替。</p>
<ul>
<li>关键词为 RIGHT JOIN 或 RIGHT OUTER JOIN</li>
</ul>
<p><strong>实例</strong>：</p>
<div class="highlight-box"autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false" contenteditable="true"data-rel="SQL"><figure class="iseeu highlight /sql"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">SELECT</span> * <span class="keyword">FROM</span> a <span class="keyword">RIGHT</span> <span class="keyword">JOIN</span> b <span class="keyword">ON</span> a.id = b.a_id ;</span><br></pre></td></tr></table></figure></div>

<table>
<thead>
<tr>
<th>id</th>
<th>name</th>
<th>a_id</th>
<th>age</th>
</tr>
</thead>
<tbody><tr>
<td>1</td>
<td>张三</td>
<td>1</td>
<td>少年</td>
</tr>
<tr>
<td>2</td>
<td>李四</td>
<td>2</td>
<td>青年</td>
</tr>
<tr>
<td>null</td>
<td>null</td>
<td>3</td>
<td>老年</td>
</tr>
</tbody></table>
<h4 id="3、内连接"><a href="#3、内连接" class="headerlink" title="3、内连接"></a>3、内连接</h4><p>指同时将两表作为参考对象，根据ON后给出的两表的条件将两表连接起来。结果则是两表同时满足ON后的条件的部分才会列出。</p>
<p><strong>实例</strong>：</p>
<div class="highlight-box"autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false" contenteditable="true"data-rel="SQL"><figure class="iseeu highlight /sql"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">SELECT</span> * <span class="keyword">FROM</span> a <span class="keyword">INNER</span> <span class="keyword">JOIN</span> b <span class="keyword">ON</span> a.id = b.a_id ;</span><br></pre></td></tr></table></figure></div>

<table>
<thead>
<tr>
<th>id</th>
<th>name</th>
<th>a_id</th>
<th>age</th>
</tr>
</thead>
<tbody><tr>
<td>1</td>
<td>张三</td>
<td>1</td>
<td>少年</td>
</tr>
<tr>
<td>2</td>
<td>李四</td>
<td>2</td>
<td>青年</td>
</tr>
</tbody></table>
<h4 id="4、完全连接"><a href="#4、完全连接" class="headerlink" title="4、完全连接"></a>4、完全连接</h4><p> 全连接其实是左连接和右连接的一个合集，也就是说他会查询出左表和右表的全部数据，匹配不上的会显示为null。</p>
<div class="highlight-box"autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false" contenteditable="true"data-rel="SQL"><figure class="iseeu highlight /sql"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">SELECT</span> * <span class="keyword">FROM</span> a <span class="keyword">FULL</span> <span class="keyword">JOIN</span> b <span class="keyword">on</span> a.id=b.a_id;</span><br></pre></td></tr></table></figure></div>



<p><strong>注意 ：MySql 数据库不支持完全连接，可以使用左连接 + union + 右连接的方式去模拟完全连接。</strong></p>
<h3 id="四、联合查询（union）"><a href="#四、联合查询（union）" class="headerlink" title="四、联合查询（union）"></a>四、联合查询（union）</h3><p>UNION 操作符用于合并两个或多个 SELECT 语句的结果集。</p>
<p>请注意：</p>
<ul>
<li>UNION 内部的 SELECT 语句必须拥有相同数量的列。</li>
<li>列也必须拥有相似的数据类型。</li>
<li>同时，每条 SELECT 语句中的列的顺序必须相同。</li>
</ul>
<p>联合查询有两种方式，分别是 union 和 union all。</p>
<p><strong>union 实例</strong>：</p>
<div class="highlight-box"autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false" contenteditable="true"data-rel="SQL"><figure class="iseeu highlight /sql"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">SELECT</span> <span class="keyword">name</span> <span class="keyword">FROM</span> a <span class="keyword">UNION</span> <span class="keyword">SELECT</span> <span class="keyword">name</span> <span class="keyword">FROM</span> b;</span><br></pre></td></tr></table></figure></div>

<p><strong>union all 实例</strong>：</p>
<div class="highlight-box"autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false" contenteditable="true"data-rel="SQL"><figure class="iseeu highlight /sql"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">SELECT</span> <span class="keyword">name</span> <span class="keyword">FROM</span> a <span class="keyword">UNION</span> <span class="keyword">ALL</span> <span class="keyword">SELECT</span> <span class="keyword">name</span> <span class="keyword">FROM</span> b;</span><br></pre></td></tr></table></figure></div>



<p>union all 命令和 union 命令几乎是等效的，不过 union all 命令会列出所有的值而 union 命令的值唯一。</p>
<h3 id="五、总结"><a href="#五、总结" class="headerlink" title="五、总结"></a>五、总结</h3><p>通常情况下，以上查询方式内连接查询会用的比较多，而基于笛卡尔积的查询查询会比较慢。</p>
<p>相比单表查询，多表查询可以覆盖更多业务场景，实际工作中，需要根据业务需求选择性的去使用。</p>
<hr>
<blockquote>
<p>2021年11月12日 稿</p>
</blockquote>

      
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